This is a table of type bigram and their frequencies. Use it to search & browse the list to learn more about your study carrel.
bigram | frequency |
---|---|
public health | 673 |
health care | 368 |
infectious diseases | 305 |
population size | 237 |
infectious disease | 165 |
population density | 157 |
united states | 152 |
social distancing | 145 |
floating population | 126 |
genetic diversity | 121 |
palliative care | 121 |
health promotion | 118 |
health services | 109 |
general population | 109 |
risk factors | 105 |
population dynamics | 105 |
new york | 101 |
herd immunity | 91 |
granted medrxiv | 91 |
author funder | 91 |
rural areas | 91 |
urban areas | 87 |
copyright holder | 76 |
made available | 76 |
version posted | 75 |
host population | 75 |
susceptible population | 75 |
hiv aids | 73 |
mental health | 71 |
doc id | 71 |
cord uid | 71 |
target population | 70 |
international license | 69 |
disease control | 67 |
population structure | 66 |
developing countries | 63 |
biological control | 62 |
critical care | 62 |
population health | 62 |
health status | 60 |
host populations | 59 |
medical care | 58 |
confirmed cases | 58 |
total number | 57 |
sir model | 57 |
may also | 56 |
growth rate | 55 |
disease transmission | 55 |
peer review | 54 |
effective population | 54 |
population migration | 53 |
primary care | 53 |
mutant spectrum | 53 |
disease ecology | 52 |
per day | 52 |
health outcomes | 51 |
human populations | 51 |
medrxiv preprint | 49 |
total population | 48 |
health problems | 48 |
health issues | 47 |
life history | 47 |
new zealand | 46 |
climate change | 46 |
community health | 46 |
united kingdom | 45 |
health systems | 45 |
new public | 45 |
bridge hosts | 45 |
disease dynamics | 45 |
population growth | 44 |
care services | 44 |
world health | 44 |
population distribution | 43 |
large number | 41 |
disease spread | 41 |
bighorn sheep | 41 |
reproduction number | 41 |
additional file | 41 |
mortality rate | 41 |
novel coronavirus | 41 |
health insurance | 40 |
york city | 40 |
animal shelters | 40 |
transmission dynamics | 40 |
cardiovascular disease | 40 |
hubei province | 40 |
avian influenza | 39 |
emerging infectious | 39 |
generation times | 39 |
student population | 39 |
rna viruses | 38 |
population genetic | 38 |
infection rates | 38 |
university students | 38 |
health needs | 38 |
infected individuals | 37 |
infected population | 37 |
model parameters | 37 |
per capita | 37 |
population sizes | 37 |
poster sessions | 37 |
global health | 37 |
case study | 36 |
young people | 36 |
disease prevalence | 36 |
supplementary material | 36 |
drug users | 35 |
generative model | 35 |
respiratory syndrome | 35 |
natural selection | 35 |
host species | 35 |
exponential growth | 35 |
bridge host | 35 |
drug use | 34 |
basic reproduction | 34 |
pst isolates | 34 |
population exposure | 34 |
income countries | 34 |
mutation rates | 34 |
pandemic influenza | 34 |
health organization | 33 |
disease virus | 33 |
cellular automata | 33 |
mutant spectra | 33 |
urban health | 33 |
systematic review | 33 |
health system | 33 |
age group | 33 |
acute respiratory | 32 |
national health | 32 |
immune system | 32 |
birth rate | 32 |
mortality rates | 32 |
polymorphism ratios | 32 |
disease prevention | 32 |
viral populations | 32 |
target populations | 31 |
compact scenario | 31 |
environmental conditions | 31 |
genetic distances | 31 |
closely related | 31 |
million people | 31 |
saharan africa | 31 |
new cases | 31 |
pst population | 31 |
high risk | 31 |
global warming | 30 |
physical distancing | 30 |
key populations | 30 |
care system | 30 |
beluga whales | 30 |
aedes aegypti | 30 |
health disparities | 29 |
lethal mutagenesis | 29 |
rna virus | 29 |
high levels | 29 |
dispersed scenario | 29 |
search query | 29 |
sequence data | 29 |
mouth disease | 29 |
epidemiological models | 29 |
immune response | 28 |
developed countries | 28 |
first wave | 28 |
see chapter | 28 |
age structure | 28 |
many countries | 28 |
control measures | 28 |
genetic variation | 28 |
population genetics | 28 |
human rights | 28 |
evolutionary history | 27 |
human health | 27 |
virus transmission | 27 |
inner city | 27 |
important role | 27 |
mathematical models | 27 |
sexually transmitted | 27 |
health centre | 27 |
disease emergence | 27 |
dynamic causal | 27 |
breast cancer | 26 |
health policy | 26 |
street youth | 26 |
urban settings | 26 |
coronavirus disease | 26 |
contact rates | 26 |
death rates | 26 |
maximum likelihood | 26 |
new infections | 26 |
will also | 26 |
rural districts | 26 |
gene flow | 26 |
communicable diseases | 25 |
posted september | 25 |
population mobility | 25 |
genetic drift | 25 |
long term | 25 |
united nations | 25 |
policy makers | 25 |
genome sequencing | 25 |
different regions | 25 |
substance use | 25 |
increased risk | 25 |
severe acute | 25 |
lockdown measures | 25 |
years old | 24 |
population flow | 24 |
genetic variants | 24 |
positive tests | 24 |
social justice | 24 |
human population | 24 |
generation time | 24 |
health risks | 24 |
years ago | 24 |
susceptible individuals | 24 |
social services | 24 |
sex workers | 24 |
influenza virus | 24 |
data analysis | 24 |
viral population | 24 |
mutation rate | 24 |
age groups | 24 |
pregnant women | 23 |
contact rate | 23 |
masked palm | 23 |
cyber space | 23 |
infectious agents | 23 |
social support | 23 |
viral quasispecies | 23 |
health education | 23 |
tasmanian devil | 23 |
primary health | 23 |
present study | 23 |
factors associated | 23 |
evolutionary processes | 23 |
even though | 23 |
socioeconomic status | 23 |
respiratory disease | 23 |
treatment population | 23 |
care providers | 23 |
land use | 22 |
recent years | 22 |
species transmission | 22 |
transmission rates | 22 |
natural capital | 22 |
infected people | 22 |
level bioethics | 22 |
immunodeficiency virus | 22 |
query data | 22 |
health professionals | 22 |
drinking water | 22 |
bayesian model | 22 |
intensive care | 22 |
myxoma virus | 22 |
health service | 22 |
life expectancy | 22 |
rapidly evolving | 21 |
will continue | 21 |
billion people | 21 |
virus infection | 21 |
maintenance host | 21 |
population clusters | 21 |
among populations | 21 |
study area | 21 |
posted may | 21 |
infected individual | 21 |
electronic supplementary | 21 |
urban population | 21 |
palm civet | 21 |
regional urban | 21 |
pst field | 21 |
molecular clock | 21 |
north america | 21 |
service delivery | 21 |
disease management | 21 |
infection rate | 21 |
will provide | 21 |
middle east | 21 |
capillaria hepatica | 21 |
family members | 21 |
ebola virus | 21 |
urban poor | 21 |
time series | 20 |
west nile | 20 |
urban rural | 20 |
public policy | 20 |
health threats | 20 |
genetic structure | 20 |
causal modelling | 20 |
population immunity | 20 |
risk factor | 20 |
chronic diseases | 20 |
underlying conditions | 20 |
less likely | 20 |
large populations | 20 |
differential equations | 20 |
wheat varieties | 20 |
social isolation | 20 |
wide range | 20 |
service providers | 20 |
better understanding | 20 |
migration attention | 20 |
chronic carriers | 20 |
term care | 20 |
immune responses | 20 |
carrying capacity | 20 |
harm reduction | 20 |
control population | 20 |
see table | 20 |
presentation will | 20 |
large numbers | 20 |
population groups | 20 |
environmental problems | 20 |
african american | 20 |
patients receiving | 20 |
rights reserved | 20 |
molecular evolution | 20 |
field isolates | 19 |
health conditions | 19 |
population heterogeneity | 19 |
spring festival | 19 |
incubation period | 19 |
population genomics | 19 |
population history | 19 |
two weeks | 19 |
people living | 19 |
social capital | 19 |
substance abuse | 19 |
large population | 19 |
confidence interval | 19 |
pathogen population | 19 |
gene expression | 19 |
mutation bias | 19 |
public attention | 19 |
distancing measures | 19 |
natural populations | 19 |
disease risk | 19 |
growth rates | 19 |
source population | 19 |
low income | 19 |
slirds model | 19 |
precision medicine | 19 |
population will | 19 |
upper respiratory | 19 |
death rate | 19 |
different populations | 19 |
bovine tuberculosis | 19 |
whenever possible | 19 |
target host | 19 |
low levels | 19 |
logarithmic derivative | 19 |
transmission rate | 19 |
domestic animals | 19 |
seir model | 19 |
phylogenetic analysis | 18 |
demographic history | 18 |
cervical cancer | 18 |
direct contact | 18 |
viral disease | 18 |
nile virus | 18 |
reuse allowed | 18 |
without permission | 18 |
high mutation | 18 |
urban environment | 18 |
san francisco | 18 |
will help | 18 |
metropolitan areas | 18 |
population infection | 18 |
allowed without | 18 |
drug treatment | 18 |
high school | 18 |
health interventions | 18 |
dengue fever | 18 |
epidemic dynamics | 18 |
genetic data | 18 |
wild populations | 18 |
food security | 18 |
entire population | 18 |
genetic distance | 18 |
migration population | 18 |
control programs | 18 |
fertility transition | 18 |
diverse populations | 18 |
epidemiological data | 18 |
child health | 18 |
ecology theory | 18 |
animal health | 18 |
phylogenetic tree | 18 |
male mutation | 18 |
average number | 18 |
syndrome coronavirus | 18 |
time step | 18 |
positive test | 18 |
humanitarian crises | 18 |
evolutionary dynamics | 18 |
surveillance system | 18 |
higher risk | 18 |
disease outbreaks | 18 |
social sciences | 17 |
care systems | 17 |
authors declare | 17 |
median age | 17 |
endangered species | 17 |
specific health | 17 |
human influenza | 17 |
model evidence | 17 |
energy expenditure | 17 |
control strategies | 17 |
resource allocation | 17 |
focus groups | 17 |
life cycle | 17 |
sea lions | 17 |
census data | 17 |
population cluster | 17 |
sea level | 17 |
communicable disease | 17 |
data collection | 17 |
colorectal cancer | 17 |
second wave | 17 |
population densities | 17 |
demographic transition | 17 |
surveillance data | 17 |
base case | 17 |
receiving dialysis | 17 |
much higher | 17 |
bat species | 17 |
common ancestor | 16 |
humanitarian emergencies | 16 |
times higher | 16 |
urban area | 16 |
cardiovascular diseases | 16 |
influenza viruses | 16 |
natural enemies | 16 |
air pollution | 16 |
chronic disease | 16 |
infectious period | 16 |
reproduction ratio | 16 |
allele frequencies | 16 |
contact tracing | 16 |
posted april | 16 |
adverse health | 16 |
human immunodeficiency | 16 |
urban centres | 16 |
wildlife populations | 16 |
phylogenetic trees | 16 |
surveillance systems | 16 |
population may | 16 |
predictive validity | 16 |
incidence data | 16 |
baidu index | 16 |
medical services | 16 |
adult population | 16 |
population decline | 16 |
urban centers | 16 |
swarming sites | 16 |
cats may | 16 |
local health | 16 |
limited resources | 16 |
food webs | 16 |
provide information | 16 |
will require | 16 |
rcd virus | 16 |
will need | 16 |
one health | 16 |
main text | 16 |
amino acid | 16 |
african americans | 16 |
host genetic | 16 |
drug resistance | 15 |
ranging dogs | 15 |
different countries | 15 |
population wellness | 15 |
health programs | 15 |
sample size | 15 |
health surveillance | 15 |
based research | 15 |
parameter estimates | 15 |
genetic differentiation | 15 |
period times | 15 |
epidemiological studies | 15 |
california sea | 15 |
mass action | 15 |
sex ratio | 15 |
social determinants | 15 |
west africa | 15 |
migration reasons | 15 |
educational level | 15 |
little influence | 15 |
i round | 15 |
urban agglomerations | 15 |
skyline plot | 15 |
wellness program | 15 |
cold chain | 15 |
based estimates | 15 |
people infected | 15 |
migrant populations | 15 |
twentieth century | 15 |
physical activity | 15 |
urban communities | 15 |
future research | 15 |
host systems | 15 |
health indicators | 15 |
devil facial | 15 |
calorie food | 15 |
field samples | 15 |
reproductive number | 15 |
experimental data | 15 |
phylogenetic methods | 15 |
health policies | 15 |
social mobility | 15 |
ethnic minority | 15 |
correlation coefficient | 15 |
rabbit populations | 15 |
water supply | 15 |
roaming dogs | 15 |
antibody testing | 15 |
technical report | 15 |
nucleotide sequences | 15 |
close contact | 15 |
risk groups | 15 |
best practices | 15 |
primary prevention | 15 |
viral rna | 15 |
vast majority | 15 |
single nucleotide | 15 |
may require | 15 |
search keywords | 15 |
genetic variability | 15 |
history traits | 15 |
positive selection | 15 |
every days | 15 |
local population | 15 |
first century | 14 |
haemorrhagic disease | 14 |
statistically significant | 14 |
health information | 14 |
reported cases | 14 |
ethical issues | 14 |
ecosystem services | 14 |
community size | 14 |
consensus sequence | 14 |
yellow fever | 14 |
principal components | 14 |
community members | 14 |
monte carlo | 14 |
model comparison | 14 |
simulation results | 14 |
insecticide application | 14 |
least one | 14 |
many factors | 14 |
transition probabilities | 14 |
two groups | 14 |
field pathogenomics | 14 |
law students | 14 |
food items | 14 |
local epidemics | 14 |
transmitted diseases | 14 |
per year | 14 |
correlation analysis | 14 |
selective pressure | 14 |
vulnerable population | 14 |
lyme disease | 14 |
results show | 14 |
urban populations | 14 |
east asia | 14 |
pharmaceutical interventions | 14 |
significantly higher | 14 |
industrialized countries | 14 |
especially important | 14 |
mobile populations | 14 |
overall population | 14 |
small populations | 14 |
homeless people | 14 |
conceptual framework | 14 |
algal blooms | 14 |
demographic density | 14 |
commonly used | 14 |
testing capacity | 14 |
pathogen transmission | 14 |
risk population | 14 |
theoretical concepts | 14 |
vertebrate pests | 14 |
nipah virus | 14 |
heart disease | 14 |
food insecurity | 14 |
reservoir hosts | 14 |
chagas disease | 14 |
former municipality | 14 |
test results | 14 |
transmission function | 14 |
mutation frequency | 14 |
random walk | 14 |
may occur | 14 |
routine testing | 14 |
available data | 14 |
st century | 14 |
migrant workers | 13 |
healthy cities | 13 |
competing interests | 13 |
population level | 13 |
peak day | 13 |
ethnic minorities | 13 |
snp sites | 13 |
plant pathogens | 13 |
us adult | 13 |
ecological systems | 13 |
civil society | 13 |
overall health | 13 |
us dialysis | 13 |
fatality rate | 13 |
injection drug | 13 |
health workers | 13 |
type diabetes | 13 |
bayesian coalescent | 13 |
stable value | 13 |
wide variety | 13 |
i think | 13 |
staphylococcus aureus | 13 |
epidemiological parameters | 13 |
may increase | 13 |
spatial coupling | 13 |
target hosts | 13 |
bayesian inference | 13 |
peak period | 13 |
early stages | 13 |
sars coronavirus | 13 |
influence coefficients | 13 |
badger culling | 13 |
vaccination program | 13 |
intervention strategies | 13 |
physical health | 13 |
aged years | 13 |
living conditions | 13 |
random sampling | 13 |
energy intake | 13 |
results suggest | 13 |
asian msm | 13 |
large proportion | 13 |
migration rates | 13 |
divergence times | 13 |
may reduce | 13 |
sample selection | 13 |
social groups | 13 |
across different | 13 |
promote health | 13 |
healthy people | 13 |
greater influence | 13 |
european bat | 13 |
two different | 13 |
scale testing | 13 |
virus extinction | 13 |
ishikawa prefecture | 13 |
environmental factors | 13 |
error catastrophe | 13 |
care needs | 13 |
research project | 13 |
large urban | 13 |
smoking cessation | 13 |
disease epidemiology | 13 |
might also | 13 |
ecological processes | 13 |
sequence space | 13 |
canine distemper | 13 |
high level | 13 |
essential workers | 13 |
viral diseases | 13 |
evolutionary biology | 13 |
population ratio | 13 |
adaptive management | 13 |
virus evolution | 13 |
high prevalence | 13 |
will allow | 13 |
host density | 12 |
birth rates | 12 |
animal populations | 12 |
data collected | 12 |
three urban | 12 |
historical changes | 12 |
people per | 12 |
tested positive | 12 |
clinical bioethics | 12 |
intercity population | 12 |
capacity building | 12 |
age distribution | 12 |
susceptible density | 12 |
findings suggest | 12 |
hong kong | 12 |
spreader cohort | 12 |
population data | 12 |
also used | 12 |
nineteenth century | 12 |
zoonotic diseases | 12 |
disadvantaged populations | 12 |
clean water | 12 |
rabies virus | 12 |
calculated using | 12 |
epidemiological dynamics | 12 |
case definitions | 12 |
los angeles | 12 |
cohort study | 12 |
epidemic models | 12 |
selection bias | 12 |
grid resolution | 12 |
host range | 12 |
health practice | 12 |
infectious individuals | 12 |
measles epidemics | 12 |
will likely | 12 |
east respiratory | 12 |
parameter values | 12 |
older people | 12 |
pest populations | 12 |
may become | 12 |
quasispecies dynamics | 12 |
global population | 12 |
eastern europe | 12 |
viral genomes | 12 |
cumulative deaths | 12 |
models used | 12 |
mitochondrial dna | 12 |
european countries | 12 |
fmdv populations | 12 |
mental illness | 12 |
second level | 12 |
beta i | 12 |
economic status | 12 |
management strategies | 12 |
model selection | 12 |
safe water | 12 |
improve health | 12 |
model structure | 12 |
dog population | 12 |
severe covid | 12 |
urban migration | 12 |
healthcare system | 12 |
relationships among | 12 |
time scale | 12 |
distemper virus | 12 |
many cases | 12 |
spatial distribution | 12 |
confidence intervals | 12 |
preventive measures | 12 |
dialysis population | 12 |
two main | 12 |
one year | 12 |
hiv infection | 12 |
i will | 12 |
ethnic groups | 12 |
antibody test | 12 |
health inequalities | 12 |
data set | 12 |
care admissions | 12 |
linear model | 12 |
local community | 12 |
global spread | 12 |
viral sequences | 12 |
deaths per | 12 |
survival probability | 12 |
recent study | 12 |
epidemics reveal | 12 |
case fatality | 12 |
rural settings | 12 |
dna sequences | 12 |
vaccination programs | 12 |
diagnosed cases | 12 |
distinct effects | 12 |
ottawa charter | 12 |
high correlation | 11 |
free energy | 11 |
population biology | 11 |
many people | 11 |
behavioral health | 11 |
recent common | 11 |
allele frequency | 11 |
infected host | 11 |
food production | 11 |
municipal health | 11 |
hospital care | 11 |
random sample | 11 |
high rates | 11 |
brown tree | 11 |
credible intervals | 11 |
higher levels | 11 |
humanitarian contexts | 11 |
tertiary prevention | 11 |
water supplies | 11 |
phylogenetic inference | 11 |
dcm parameters | 11 |
zoonotic disease | 11 |
compartmental models | 11 |
infected person | 11 |
false positives | 11 |
past years | 11 |
people aged | 11 |
farm populations | 11 |
molecular epidemiology | 11 |
individual health | 11 |
free choice | 11 |
geographical space | 11 |
latin america | 11 |
world bank | 11 |
wild animals | 11 |
emerging pathogens | 11 |
resource limitations | 11 |
individuals within | 11 |
host genotypes | 11 |
factors affecting | 11 |
search engine | 11 |
genetic testing | 11 |
human genome | 11 |
technological system | 11 |
puccinia striiformis | 11 |
vice versa | 11 |
economically disadvantaged | 11 |
case studies | 11 |
social contact | 11 |
economic structure | 11 |
natural history | 11 |
maintenance function | 11 |
high mortality | 11 |
western barred | 11 |
data sources | 11 |
integral part | 11 |
rabbit haemorrhagic | 11 |
green turtles | 11 |
three main | 11 |
high frequency | 11 |
contacts per | 11 |
nucleotide sequence | 11 |
posted june | 11 |
infected wheat | 11 |
universal health | 11 |
virulence profiles | 11 |
wheat variety | 11 |
probability distribution | 11 |
sequence alignment | 11 |
remainder plasma | 11 |
heart failure | 11 |
drug abuse | 11 |
will increase | 11 |
clinical outcomes | 11 |
small number | 11 |
last years | 11 |
inflow population | 11 |
diverse local | 11 |
mixing patterns | 11 |
conservation biology | 11 |
model based | 11 |
developing world | 11 |
control agents | 11 |
ltc residents | 11 |
mutation frequencies | 11 |
autoimmune diseases | 11 |
domestic cats | 11 |
differences among | 11 |
body condition | 11 |
previous studies | 11 |
respiratory infections | 11 |
human evolution | 11 |
ensemble dynamics | 11 |
individuals may | 11 |
human immune | 11 |
commercially available | 11 |
unwanted sexual | 11 |
relatively large | 11 |
allows us | 11 |
blood pressure | 11 |
vector control | 11 |
term housing | 11 |
epidemic spread | 11 |
results indicate | 11 |
compartmental model | 11 |
rate constant | 11 |
vulnerable populations | 11 |
asylum seekers | 11 |
wildlife species | 11 |
people will | 11 |
mouse populations | 11 |
domestic dogs | 11 |
high population | 11 |
dog populations | 11 |
population disease | 11 |
private sector | 11 |
good health | 11 |
community capacity | 11 |
generation interval | 11 |
african wild | 11 |
environmental health | 11 |
among components | 11 |
rural locations | 11 |
health survey | 11 |
public policies | 11 |
natural resources | 11 |
focus group | 11 |
first step | 11 |
final size | 11 |
wildlife disease | 10 |
polymorphism ratio | 10 |
fertility control | 10 |
interactions among | 10 |
health authorities | 10 |
new immigrants | 10 |
leaving home | 10 |
online version | 10 |
migrant health | 10 |
international travel | 10 |
maintenance population | 10 |
care unit | 10 |
facial tumour | 10 |
crucial role | 10 |
priority groups | 10 |
data will | 10 |
logistic regression | 10 |
observed data | 10 |
true positive | 10 |
antibiotic resistance | 10 |
epidemic model | 10 |
mathematical modeling | 10 |
among individuals | 10 |
seasonal influenza | 10 |
monitoring survey | 10 |
york times | 10 |
expected number | 10 |
modelling study | 10 |
family history | 10 |
significantly lower | 10 |
federal government | 10 |
broad range | 10 |
population centers | 10 |
markov chain | 10 |
demographic data | 10 |
several different | 10 |
th century | 10 |
paper will | 10 |
nutritional status | 10 |
contains supplementary | 10 |
data used | 10 |
pilot study | 10 |
international migration | 10 |
health targets | 10 |
much lower | 10 |
nan doi | 10 |
international health | 10 |
health literacy | 10 |
preventive care | 10 |
brown bullhead | 10 |
mobility restrictions | 10 |
reproductive variances | 10 |
cases per | 10 |
wellness programs | 10 |
study will | 10 |
sexual abuse | 10 |
crack users | 10 |
allow us | 10 |
infection dynamics | 10 |
mathematical model | 10 |
susceptible hosts | 10 |
sensitivity analysis | 10 |
health problem | 10 |
disease severity | 10 |
nuclear families | 10 |
clinical medicine | 10 |
super spreader | 10 |
health research | 10 |
error threshold | 10 |
survey data | 10 |
rates across | 10 |
positive correlation | 10 |
future population | 10 |
tree snake | 10 |
measles transmission | 10 |
precision dosing | 10 |
sle beluga | 10 |
journal rsif | 10 |
bayesian phylogenetic | 10 |
infection status | 10 |
different species | 10 |
maximum number | 10 |
tumour disease | 10 |
measles vaccine | 10 |
will focus | 10 |
high incidence | 10 |
large scale | 10 |
public migration | 10 |
borne diseases | 10 |
community structure | 10 |
higher rates | 10 |
statistical models | 10 |
fruit bats | 10 |
wild bird | 10 |
testing every | 10 |
health organizations | 10 |
metapopulation models | 10 |
health impacts | 10 |
give rise | 10 |
will vary | 10 |
healthcare workers | 10 |
festival holiday | 10 |
four population | 10 |
mixing rates | 10 |
case finding | 10 |
rapid spread | 10 |
population prevalence | 10 |
first time | 10 |
sample sizes | 10 |
western europe | 10 |
community transmission | 10 |
reproductive health | 10 |
less developed | 10 |
basic reproductive | 10 |
distances among | 10 |
prevalence estimates | 10 |
tasmanian devils | 10 |
org journal | 10 |
widely used | 10 |
fatality rates | 10 |
community services | 10 |
model used | 10 |
help us | 10 |
different levels | 10 |
resistant staphylococcus | 10 |
will result | 10 |
viral genome | 10 |
management outcomes | 10 |
occupational health | 10 |
healthcare services | 10 |
better health | 10 |
mutations per | 10 |
astrovirus sequences | 10 |
relative metabolic | 10 |
animal shelter | 10 |
maintenance community | 10 |
genetic analysis | 10 |
health protection | 10 |
south asia | 10 |
european ancestry | 10 |
health agencies | 10 |
transmission may | 10 |
among different | 10 |
one hand | 10 |
infections per | 10 |
low genetic | 10 |
animal welfare | 10 |
two years | 9 |
biofuel production | 9 |
health consequences | 9 |
applied biosystems | 9 |
first two | 9 |
positive rate | 9 |
sequencing data | 9 |
health planning | 9 |
urban districts | 9 |
university student | 9 |
global trends | 9 |
enhanced mutagenesis | 9 |
level rise | 9 |
potential bridge | 9 |
adult cats | 9 |
local scale | 9 |
health facilities | 9 |
viral species | 9 |
author recommends | 9 |
become part | 9 |
transmission within | 9 |
health law | 9 |
prevent disease | 9 |
human activities | 9 |
world population | 9 |
cats will | 9 |
astrovirus haplotypes | 9 |
disease surveillance | 9 |
different groups | 9 |
bat host | 9 |
immune receptor | 9 |
field sample | 9 |
particular population | 9 |
arthropod vectors | 9 |
mortality incidence | 9 |
future studies | 9 |
estimate population | 9 |
mathematical theory | 9 |
social policy | 9 |
chain monte | 9 |
may provide | 9 |
control efforts | 9 |
technological systems | 9 |
polymerase chain | 9 |
several studies | 9 |
geographic regions | 9 |
daily deaths | 9 |
delphinapterus leucas | 9 |
adverse effects | 9 |
african population | 9 |
test result | 9 |
among children | 9 |
myotis nattereri | 9 |
multihost systems | 9 |
simulation experiments | 9 |
three times | 9 |
consensus sequences | 9 |
empirical data | 9 |
statistical methods | 9 |
demographic characteristics | 9 |
per million | 9 |
strain type | 9 |
improved health | 9 |
health context | 9 |
contact patterns | 9 |
sexual health | 9 |
wellness protocols | 9 |
significant difference | 9 |
universal access | 9 |
us population | 9 |
microsatellite loci | 9 |
xx xx | 9 |
metropolitan region | 9 |
using bayesian | 9 |
mean field | 9 |
authorized users | 9 |
one host | 9 |
municipality model | 9 |
among people | 9 |
supreme court | 9 |
highly variable | 9 |
model also | 9 |
vary depending | 9 |
purifying selection | 9 |
viral spread | 9 |
parasite population | 9 |
average value | 9 |
evolutionary rates | 9 |
become infected | 9 |
critically ill | 9 |
synonymous mutations | 9 |
policy development | 9 |
barred bandicoots | 9 |
wild birds | 9 |
health measures | 9 |
spatial patterns | 9 |
also important | 9 |
seroprevalence surveys | 9 |
molecular sequences | 9 |
may result | 9 |
low level | 9 |
genomic data | 9 |
genetic algorithm | 9 |
across populations | 9 |
healthy city | 9 |
birth weight | 9 |
hiv prevalence | 9 |
model predictions | 9 |
methods used | 9 |
metapopulation dynamics | 9 |
year age | 9 |
international migrants | 9 |
given time | 9 |
evolving viruses | 9 |
urban environments | 9 |
generation sequencing | 9 |
model using | 9 |
coalescent theory | 9 |
community development | 9 |
many years | 9 |
floating populations | 9 |
poor health | 9 |
young children | 9 |
diversity within | 9 |
must also | 9 |
bioethics lens | 9 |
infected hosts | 9 |
african populations | 9 |
social behavior | 9 |
responsive behaviour | 9 |
physical environment | 9 |
animal species | 9 |
birth interval | 9 |
higher level | 9 |
complex substances | 9 |
aged cities | 9 |
human behavior | 9 |
ovis canadensis | 9 |
influenza pandemic | 9 |
genetically distinct | 9 |
viral replication | 9 |
health implications | 9 |
case data | 9 |
weighted average | 9 |
genetic markers | 9 |
appendix table | 9 |
may reflect | 9 |
reduce disease | 9 |
zero population | 9 |
prevent transmission | 9 |
economic development | 9 |
low education | 9 |
per population | 9 |
million cases | 9 |
tropical diseases | 9 |
reservoir host | 9 |
palm civets | 9 |
peak point | 9 |
specific humidity | 9 |
cell receptor | 9 |
mycoplasma ovipneumoniae | 9 |
random testing | 9 |
household registration | 9 |
within populations | 9 |
specific life | 9 |
wildlife health | 9 |
significantly associated | 9 |
metropolitan regions | 9 |
secondary prevention | 9 |
archaeological data | 9 |
greater risk | 9 |
preventive medicine | 9 |
attack rate | 9 |
risk assessment | 9 |
health crisis | 9 |
health determinants | 8 |
comparative analysis | 8 |
first one | 8 |
maintenance hosts | 8 |
may lead | 8 |
cancer screening | 8 |
populations may | 8 |
care facilities | 8 |
coalescent framework | 8 |
group housing | 8 |
measles virus | 8 |
red deer | 8 |
long time | 8 |
diffusion coefficient | 8 |
individual movement | 8 |
solid waste | 8 |
genealogical ratios | 8 |
projection model | 8 |
north american | 8 |
correlation coefficients | 8 |
side effects | 8 |
systems biology | 8 |
different types | 8 |
air quality | 8 |
animal care | 8 |
per month | 8 |
social exclusion | 8 |
exposure metric | 8 |
river delta | 8 |
dynamic monitoring | 8 |
given population | 8 |
virus population | 8 |
study period | 8 |
neolithic demographic | 8 |
period march | 8 |
may need | 8 |
using data | 8 |
coronavirus pandemic | 8 |
diagnostic uncertainty | 8 |
infected persons | 8 |
mortality data | 8 |
quarantine measures | 8 |
new urban | 8 |
south america | 8 |
nucleotide polymorphisms | 8 |
several factors | 8 |
microsatellite markers | 8 |
time period | 8 |
assessed using | 8 |
syndromic surveillance | 8 |
elderly people | 8 |
will depend | 8 |
three regions | 8 |
pest control | 8 |
will occur | 8 |
peak infections | 8 |
human infection | 8 |
health effects | 8 |
human beings | 8 |
health impact | 8 |
access health | 8 |
population rap | 8 |
cell culture | 8 |
based surveillance | 8 |
critical community | 8 |
leading cause | 8 |
recent studies | 8 |
corona crisis | 8 |
past months | 8 |
epidemic will | 8 |
south dakota | 8 |
infectious agent | 8 |
across locations | 8 |
pk pd | 8 |
urban migrants | 8 |
sarcophilus harrisii | 8 |
new environment | 8 |
social workers | 8 |
causative agent | 8 |
densely populated | 8 |
high turnover | 8 |
may affect | 8 |
adaptive immune | 8 |
nonlinear model | 8 |
transmission events | 8 |
slum settlements | 8 |
often used | 8 |
doubling time | 8 |
also known | 8 |
ad value | 8 |
significant differences | 8 |
recently developed | 8 |
shannon entropy | 8 |
per cent | 8 |
virus replication | 8 |
cystic fibrosis | 8 |
ascend clinical | 8 |
key role | 8 |
scientific advances | 8 |
sample collection | 8 |
health aspects | 8 |
evolutionary pressure | 8 |
genetically engineered | 8 |
different sex | 8 |
criminal justice | 8 |
sex ratios | 8 |
older adults | 8 |
infectious contacts | 8 |
national estimates | 8 |
decision making | 8 |
vaccination campaigns | 8 |
energy balance | 8 |
ebola outbreak | 8 |
personal communication | 8 |
sexual behavior | 8 |
resource availability | 8 |
civet populations | 8 |
study showed | 8 |
pathogen surveillance | 8 |
information systems | 8 |
frequency data | 8 |
history parameters | 8 |
short time | 8 |
epidemic growth | 8 |
national land | 8 |
european rabbit | 8 |
health risk | 8 |
month period | 8 |
population control | 8 |
health officials | 8 |
wastewater treatment | 8 |
european rabbits | 8 |
fisher model | 8 |
critical role | 8 |
test positive | 8 |
disease systems | 8 |
holistic approach | 8 |
standard deviation | 8 |
epidemic forecasting | 8 |
large cities | 8 |
big data | 8 |
small sample | 8 |
prairie chickens | 8 |
viral infections | 8 |
inflammatory bowel | 8 |
health concerns | 8 |
women living | 8 |
general public | 8 |
complex components | 8 |
migrant population | 8 |
major cause | 8 |
spread process | 8 |
important consideration | 8 |
testing strategies | 8 |
human disease | 8 |
population management | 8 |
rate per | 8 |
state space | 8 |
across regions | 8 |
chain reaction | 8 |
provincial level | 8 |
antiretroviral therapy | 8 |
social service | 8 |
managed care | 8 |
medical treatment | 8 |
molecular clones | 8 |
uk population | 8 |
population bottlenecks | 8 |
vertebrate pest | 8 |
important implications | 8 |
among women | 8 |
capacity coefficient | 8 |
limited number | 8 |
evolutionary analysis | 8 |
seq data | 8 |
spread rapidly | 8 |
randomly selected | 8 |
modern humans | 8 |
environmental changes | 8 |
health benefits | 8 |
will become | 8 |
mortality growth | 8 |
mg kg | 8 |
wild dogs | 8 |
visceral leishmaniasis | 8 |
risk group | 8 |
many different | 8 |
breeding colonies | 8 |
pst lineages | 8 |
reduce covid | 8 |
kidney disease | 8 |
sexual experiences | 8 |
virus type | 8 |
group i | 8 |
model averaging | 8 |
health challenges | 8 |
child mortality | 8 |
mobility data | 8 |
community action | 8 |
legal analysis | 8 |
hospital admissions | 8 |
census population | 8 |
one third | 8 |
law school | 8 |
sex type | 8 |
final manuscript | 8 |
based model | 8 |
every day | 8 |
mental disorders | 8 |
environmental change | 8 |
rates among | 8 |
demographic factors | 8 |
significant effect | 8 |
overall trend | 8 |
health activities | 8 |
vertical transmission | 8 |
single population | 8 |
pediatric patients | 8 |
metabolic load | 8 |
feral cats | 8 |
transmission patterns | 8 |
genomic sequences | 8 |
much less | 8 |
linear regression | 8 |
bayesian skyline | 8 |
areas may | 8 |
compartment model | 8 |
population based | 8 |
information criterion | 8 |
current health | 8 |
data available | 8 |
fit model | 7 |
case counts | 7 |
escherichia coli | 7 |
rural household | 7 |
preventing disease | 7 |
family planning | 7 |
local authorities | 7 |
clinical features | 7 |
exponential rate | 7 |
post hoc | 7 |
country level | 7 |
see discussion | 7 |
free environments | 7 |
zona pellucida | 7 |
super spreaders | 7 |
emergent pst | 7 |
antigenic variants | 7 |
testing rate | 7 |
contact network | 7 |
issues related | 7 |
trophic levels | 7 |
wildlife diseases | 7 |
phylogenetic analyses | 7 |
approach will | 7 |
viral evolution | 7 |
spread model | 7 |
early diagnosis | 7 |
chelonia mydas | 7 |
host community | 7 |
epidemic outbreak | 7 |
right side | 7 |
behaviour triggers | 7 |
quantitative data | 7 |
information storage | 7 |
family physicians | 7 |
health monitoring | 7 |
related health | 7 |
decision makers | 7 |
deep sequencing | 7 |
coalescence rates | 7 |
safe drinking | 7 |
overlay analysis | 7 |
bad test | 7 |
first group | 7 |
variational free | 7 |
birth timing | 7 |
first year | 7 |
neglected tropical | 7 |
global public | 7 |
key factors | 7 |
disease model | 7 |
hiv epidemic | 7 |
health hazards | 7 |
identify potential | 7 |
transmission history | 7 |
whole population | 7 |
future generations | 7 |
yellow rust | 7 |
higher values | 7 |
infant mortality | 7 |
based participatory | 7 |
job opportunities | 7 |
growth model | 7 |
social medicine | 7 |
one another | 7 |
care must | 7 |
healthy environment | 7 |
different urban | 7 |
immunity threshold | 7 |
one person | 7 |
pathogen sequences | 7 |
cvd risk | 7 |
parameter estimation | 7 |
advocacy groups | 7 |
effective control | 7 |
health sector | 7 |
respiratory infection | 7 |
legal issues | 7 |
existing health | 7 |
community based | 7 |
abuse treatment | 7 |
simple model | 7 |
infected field | 7 |
prevalence among | 7 |
single infected | 7 |
study conducted | 7 |
partition analysis | 7 |
street health | 7 |
particularly important | 7 |
adult cities | 7 |
also considered | 7 |
cefepime concentrations | 7 |
chemical pollution | 7 |
many instances | 7 |
leukemia virus | 7 |
two populations | 7 |
determine whether | 7 |
single pst | 7 |
statistical computing | 7 |
genetic adaptation | 7 |
mosquito population | 7 |
maximum mutation | 7 |
natural environment | 7 |
nuclear dna | 7 |
social conditions | 7 |
three different | 7 |
lycaon pictus | 7 |
bullhead catfish | 7 |
coding region | 7 |
three groups | 7 |
structured coalescent | 7 |
social environment | 7 |
one city | 7 |
national level | 7 |
isolation areas | 7 |
individual genomes | 7 |
breeding catteries | 7 |
per unit | 7 |
respiratory viruses | 7 |
outpatient care | 7 |
population grids | 7 |
examples include | 7 |
per week | 7 |
different states | 7 |
professional organizations | 7 |
two indexes | 7 |
gravity model | 7 |
worm infections | 7 |
mechanistic models | 7 |
acquired immunity | 7 |
level data | 7 |
highly centralised | 7 |
new cats | 7 |
social graph | 7 |
rabies control | 7 |
previous research | 7 |
lower bound | 7 |
prevention behaviours | 7 |
phenotypic characteristics | 7 |
control populations | 7 |
virus mutant | 7 |
contained within | 7 |
areas will | 7 |
racial ethnic | 7 |
spatial population | 7 |
family medicine | 7 |
among immigrants | 7 |
rapid population | 7 |
community involvement | 7 |
within municipalities | 7 |
data sets | 7 |
intervention group | 7 |
history effects | 7 |
related individuals | 7 |
clock model | 7 |
will remain | 7 |
manuscript writing | 7 |
sterile syringes | 7 |
experimental infection | 7 |
health response | 7 |
environmental management | 7 |
may include | 7 |
well known | 7 |
disease burden | 7 |
long distances | 7 |
birth control | 7 |
respiratory distress | 7 |
rural populations | 7 |
health providers | 7 |
health commission | 7 |
major role | 7 |
healthy public | 7 |
environmental contamination | 7 |
transition towards | 7 |
cumulative mortality | 7 |
informed consent | 7 |
marginal likelihood | 7 |
host genotype | 7 |
also found | 7 |
substitution models | 7 |
transmitted infections | 7 |
preventable diseases | 7 |
zalophus californianus | 7 |
premature mortality | 7 |
clinical signs | 7 |
southeast asia | 7 |
geographic origin | 7 |
sierra leone | 7 |
disease research | 7 |
global scale | 7 |
different factors | 7 |
population parameter | 7 |
downtown toronto | 7 |
also include | 7 |
nucleotide polymorphism | 7 |
pk model | 7 |
economic factors | 7 |
service provision | 7 |
previously described | 7 |
vital role | 7 |
care access | 7 |
hiv disease | 7 |
college students | 7 |
transmission model | 7 |
population diversity | 7 |
pathogenomics approach | 7 |
prenatal care | 7 |
chronic wasting | 7 |
inflammatory diseases | 7 |
paguma larvata | 7 |
wasting disease | 7 |
transmission pathways | 7 |
health intervention | 7 |
also provide | 7 |
spatial proximity | 7 |
linkage disequilibrium | 7 |
specific mortality | 7 |
aromatic hydrocarbons | 7 |
relatively high | 7 |
risk populations | 7 |
four levels | 7 |
odds ratio | 7 |
national governments | 7 |
six months | 7 |
diversity levels | 7 |
economic growth | 7 |
phylogenetic relationships | 7 |
kanazawa city | 7 |
taken together | 7 |
internal migration | 7 |
community ecology | 7 |
different migration | 7 |
nasal swab | 7 |
aged people | 7 |
underlying disease | 7 |
mathematical epidemiology | 7 |
molecular data | 7 |
south africa | 7 |
us department | 7 |
health powers | 7 |
time point | 7 |
respiratory tract | 7 |
many others | 7 |
human host | 7 |
initial conditions | 7 |
health efforts | 7 |
ethiopian wolf | 7 |
small intestinal | 7 |
takes place | 7 |
humanitarian response | 7 |
data may | 7 |
working population | 7 |
standard errors | 7 |
needle exchange | 7 |
analyzed using | 7 |
treatment services | 7 |
city planning | 7 |
influence coefficient | 7 |
two distinct | 7 |
many ways | 7 |
may take | 7 |
infections caused | 7 |
wild type | 7 |
i i | 7 |
housing arrangements | 7 |
social networks | 7 |
viruses may | 7 |
tsir model | 7 |
evolutionary theory | 7 |
care resources | 7 |
left panel | 7 |
social work | 7 |
new areas | 7 |
new approach | 7 |
johns hopkins | 7 |
global community | 7 |
household registers | 7 |
machine learning | 7 |
phylodynamic inference | 7 |
democratic republic | 7 |
minority immigrants | 7 |
limited access | 7 |
hiding place | 7 |
international organizations | 7 |
resistance genes | 7 |
individual patients | 7 |
population setting | 7 |
healthcare providers | 7 |
care may | 7 |
specific disease | 7 |
every individual | 7 |
highly correlated | 7 |
differential equation | 7 |
russian economy | 7 |
pathogen evolution | 7 |
research council | 7 |
profound impact | 7 |
dynamical systems | 7 |
seasonal transmission | 7 |
physician visits | 7 |
took place | 7 |
many cats | 7 |
two wild | 7 |
clock models | 7 |
housing cats | 7 |
ecosystem matrix | 7 |
theoretical basis | 7 |
putative virus | 7 |
actual number | 7 |
among older | 7 |
vaccination strategies | 7 |
epidemic situation | 7 |
early detection | 7 |
care capacity | 7 |
external factors | 7 |
aquatic phase | 7 |
homogeneous population | 7 |
comprehensive approach | 7 |
research process | 7 |
law schools | 7 |
illicit drug | 7 |
mitigation strategies | 7 |
ecological approaches | 7 |
relatively lower | 7 |
within hubei | 7 |
conditional dependencies | 7 |
unrestricted dogs | 7 |
study also | 7 |
many species | 7 |
social security | 7 |
rapid evolution | 7 |
former soviet | 7 |
sea lion | 7 |
hospitalized patients | 7 |
host specificity | 7 |
aids epidemic | 7 |
community partners | 7 |
model development | 7 |
tailed deer | 7 |
parametric empirical | 7 |
evolutionary adaptation | 6 |
tuberculosis control | 6 |
human right | 6 |
working group | 6 |
state university | 6 |
ethiopian wolves | 6 |
made possible | 6 |
molecular cloning | 6 |
diagnostic tools | 6 |
infected cases | 6 |
living area | 6 |
preventive health | 6 |
health field | 6 |
adversely affect | 6 |
functional form | 6 |
upper limit | 6 |
personal health | 6 |
disease resistance | 6 |
external areas | 6 |
high quality | 6 |
er op | 6 |
chart review | 6 |
zip code | 6 |
knowledge scores | 6 |
generation intervals | 6 |
serial interval | 6 |
healthcare demand | 6 |
may differ | 6 |
african countries | 6 |
pcr testing | 6 |
population per | 6 |
ratio coefficient | 6 |
reduce risk | 6 |
footed ferrets | 6 |
physical examination | 6 |
peripheral blood | 6 |
acute infections | 6 |
host evolution | 6 |
domestic cat | 6 |
one example | 6 |
exact test | 6 |
hispanic white | 6 |
time evolution | 6 |
towards higher | 6 |
public good | 6 |
mortality among | 6 |
susceptible state | 6 |
stroke prevention | 6 |
several ways | 6 |
disabled children | 6 |
pain relief | 6 |
prior knowledge | 6 |
spread across | 6 |
small mammals | 6 |
body weight | 6 |
care delivery | 6 |
first stage | 6 |
highest rates | 6 |
recent changes | 6 |
immunization population | 6 |
diabetes mellitus | 6 |
vaccine allocation | 6 |
populations around | 6 |
technological exposure | 6 |
contact networks | 6 |
population crashes | 6 |
performed using | 6 |
crf ag | 6 |
reservoir capacity | 6 |
areas within | 6 |
paq analysis | 6 |
studies indicate | 6 |
new methods | 6 |
characteristic time | 6 |
simulations show | 6 |
apparently healthy | 6 |
high sensitivity | 6 |
voluntary sector | 6 |
will lead | 6 |
pet ownership | 6 |
time distribution | 6 |
industrial revolution | 6 |
substitution rate | 6 |
disease may | 6 |
receptor recognition | 6 |
bat populations | 6 |
closely linked | 6 |
migration health | 6 |
biological evolution | 6 |
lethal defection | 6 |
day changes | 6 |
immunogenomics studies | 6 |
institutional reform | 6 |
control group | 6 |
variety aa | 6 |
exotic pst | 6 |
based health | 6 |
testing regime | 6 |
may remain | 6 |
rna sequencing | 6 |
millennium development | 6 |
transgender people | 6 |
component analysis | 6 |
geographic spread | 6 |
first level | 6 |
throughput sequencing | 6 |
patch mixing | 6 |
community participation | 6 |
minority groups | 6 |
task force | 6 |
general linear | 6 |
contact reduction | 6 |
disease caused | 6 |
genetic co | 6 |
assisted dying | 6 |
whereas others | 6 |
time interval | 6 |
expression profiles | 6 |
release rate | 6 |
short term | 6 |
chronic conditions | 6 |
similar results | 6 |
evolutionary genetics | 6 |
populations will | 6 |
adverse effect | 6 |
positively reflect | 6 |
environmental science | 6 |
provide evidence | 6 |
qualitative study | 6 |
emerging viruses | 6 |
three major | 6 |
also includes | 6 |
total amount | 6 |
us census | 6 |
urban residents | 6 |
within urban | 6 |
attention indexes | 6 |
social activity | 6 |
ethical debate | 6 |
increasing population | 6 |
extreme case | 6 |
driving force | 6 |
antibody tests | 6 |
will discuss | 6 |
police powers | 6 |
mean age | 6 |
rate coefficient | 6 |
evidence base | 6 |
social structure | 6 |
will probably | 6 |
high exposure | 6 |
spectrum complexity | 6 |
medical resources | 6 |
seroprevalence estimates | 6 |
reproductive rates | 6 |
right panel | 6 |
individual rights | 6 |
good governance | 6 |
bowel disease | 6 |
research questions | 6 |
population model | 6 |
assisted suicide | 6 |
high fitness | 6 |
new orleans | 6 |
genomic analysis | 6 |
research center | 6 |
evolutionary epidemiology | 6 |
gene frequency | 6 |
isolation measures | 6 |
prevention strategies | 6 |
darwinian selection | 6 |
participatory research | 6 |
zika virus | 6 |
health expenditure | 6 |
total infected | 6 |
refugee camp | 6 |
communicability parameter | 6 |
undersea cables | 6 |
modern migration | 6 |
health advocacy | 6 |
host country | 6 |
saudi arabia | 6 |
generalized skyline | 6 |
transmission among | 6 |
vaccine prioritization | 6 |
grids covered | 6 |
receiving nations | 6 |
improved nutrition | 6 |
wild population | 6 |
equitable access | 6 |
replacement therapy | 6 |
certain circumstances | 6 |
psychological distress | 6 |
microhaplotype loci | 6 |
two decades | 6 |
parasite genotypes | 6 |
prevention efforts | 6 |
effector proteins | 6 |
missing data | 6 |
hiv type | 6 |
phylodynamic methods | 6 |
southern african | 6 |
previous findings | 6 |
gradually stable | 6 |
publicly available | 6 |
years later | 6 |
renal disease | 6 |
clinical care | 6 |
may exhibit | 6 |
high rate | 6 |
poor countries | 6 |
independent variables | 6 |
financial support | 6 |
colonies within | 6 |
critically endangered | 6 |
great lakes | 6 |
sampling dates | 6 |
pairwise genetic | 6 |
inject drugs | 6 |
also help | 6 |
persistent infections | 6 |
temporal changes | 6 |
data transmission | 6 |
public sector | 6 |
secondary school | 6 |
current data | 6 |
cancer prevalence | 6 |
heterogeneous scenario | 6 |
persistent infection | 6 |
positive cases | 6 |
developed world | 6 |
sequencing technologies | 6 |
high blood | 6 |
epidemiological information | 6 |
human mobility | 6 |
capita living | 6 |
pst isolate | 6 |
genetic information | 6 |
geographic information | 6 |
student contacts | 6 |
will describe | 6 |
human transmission | 6 |
transmission cycle | 6 |
whole genome | 6 |
important health | 6 |
negative selection | 6 |
incremental infections | 6 |
open source | 6 |
economic conditions | 6 |
highly accurate | 6 |
initial population | 6 |
distinct lineages | 6 |
components analysis | 6 |
laboratory animals | 6 |
sus scrofa | 6 |
papanicolau tests | 6 |
child care | 6 |
term population | 6 |
contact time | 6 |
native species | 6 |
horizontal transmission | 6 |
legal education | 6 |
roaming dog | 6 |
population infections | 6 |
high cancer | 6 |
higher external | 6 |
hispanic black | 6 |
immunization programs | 6 |
providing health | 6 |
population remains | 6 |
op visits | 6 |
pcr products | 6 |
working conditions | 6 |
rural population | 6 |
genetic clusters | 6 |
new jersey | 6 |
bat lyssavirus | 6 |
field experiments | 6 |
latent states | 6 |
older uk | 6 |
isolates within | 6 |
transmissible venereal | 6 |
new data | 6 |
nombre virus | 6 |
state level | 6 |
copying fidelity | 6 |
turtle fibropapillomatosis | 6 |
population within | 6 |
secondary infections | 6 |
disease patterns | 6 |
disease progression | 6 |
allelic variants | 6 |
daily cases | 6 |
heat wave | 6 |
population regulation | 6 |
filamentous plant | 6 |
social protection | 6 |
hubei wild | 6 |
may contribute | 6 |
transmission across | 6 |
storm surges | 6 |
viral genetic | 6 |
recovery rate | 6 |
life stage | 6 |
molecular evolutionary | 6 |
lawrence river | 6 |
waste management | 6 |
study aimed | 6 |
human movement | 6 |
provide useful | 6 |
social organization | 6 |
fitness landscapes | 6 |
vulnerable groups | 6 |
virus disease | 6 |
underserved populations | 6 |
relative risk | 6 |
mask wearing | 6 |
reducing health | 6 |
time scales | 6 |
conserved among | 6 |
reference genome | 6 |
individuals will | 6 |
school calendar | 6 |
management practices | 6 |
homogeneous case | 6 |
emerging pathogen | 6 |
widely accepted | 6 |
will take | 6 |
sex chromosomes | 6 |
individual variation | 6 |
may help | 6 |
help identify | 6 |
ethnographic data | 6 |
nucleoside analogues | 6 |
false negatives | 6 |
structured metapopulation | 6 |
body mass | 6 |
epidemic disease | 6 |
current pandemic | 6 |
per se | 6 |
warming climate | 6 |
leading causes | 6 |
models containing | 6 |
populations rap | 6 |
us counties | 6 |
population estimates | 6 |
race ethnicity | 6 |
high density | 6 |
global economy | 6 |
poor environmental | 6 |
generalized linear | 6 |
health center | 6 |
compare different | 6 |
past population | 6 |
disease process | 6 |
genotype data | 6 |
collected data | 6 |
molecular biology | 6 |
treated populations | 6 |
small population | 6 |
resources available | 6 |
care advisors | 6 |
become increasingly | 6 |
developed nations | 6 |
longer term | 6 |
immigrant population | 6 |
mycobacterium bovis | 6 |
broad street | 6 |
production capacity | 6 |
analysis using | 6 |
low rates | 6 |
mus musculus | 6 |
control program | 6 |
aquatic animals | 6 |
evolution may | 6 |
health prevention | 6 |
populated areas | 6 |
public opinion | 6 |
health sciences | 6 |
bacterial infections | 6 |
highly contagious | 6 |
driven contact | 6 |
nine different | 6 |
transmission route | 6 |
relaxed clock | 6 |
social network | 6 |
care settings | 6 |
community composition | 6 |
another example | 6 |
health also | 6 |
among countries | 6 |
disease susceptibility | 6 |
bottleneck transfers | 6 |
risk approach | 6 |
express public | 6 |
harmful algal | 6 |
immune status | 6 |
life histories | 6 |
may cause | 6 |
modern public | 6 |
actual data | 6 |
hopkins university | 6 |
medical research | 6 |
response team | 6 |
home based | 6 |
linked sites | 6 |
health priorities | 6 |
lessons learned | 6 |
population dynamic | 6 |
canine transmissible | 6 |
structure analyses | 6 |
wide association | 6 |
southern china | 6 |
war ii | 6 |
selective pressures | 6 |
significant correlations | 6 |
bat lyssaviruses | 6 |
parasite genotype | 6 |
urban dwellers | 6 |
exotic vertebrates | 6 |
adverse outcomes | 6 |
fixed effects | 6 |
primary education | 6 |
european populations | 6 |
safe sex | 6 |
regional population | 6 |
two individuals | 6 |
will affect | 6 |
science foundation | 6 |
preliminary report | 6 |
testing positive | 6 |
disease outbreak | 6 |
screening programs | 6 |
particular disease | 6 |
dengue virus | 6 |
two sets | 6 |
maternal antibody | 6 |
principal component | 6 |
wildlife population | 6 |
potential impact | 6 |
relatively small | 6 |
bayesian evolutionary | 6 |
humanitarian settings | 6 |
relatively low | 6 |
health related | 6 |
vaccine development | 6 |
stochastic models | 6 |
dn ds | 6 |
social policies | 6 |
ordinary differential | 6 |
children aged | 6 |
health doi | 6 |
theoretical models | 6 |
best fit | 6 |
central africa | 6 |
immunization coverage | 6 |
natural systems | 6 |
asymptomatic infections | 6 |
world war | 6 |
ceu relative | 6 |
testing everyone | 6 |
better understand | 6 |
genomic medicine | 6 |
sexually abused | 6 |
sample period | 6 |
large fraction | 6 |
based interventions | 6 |
effective interventions | 6 |
many settings | 6 |
brushtail possums | 6 |
interventions aimed | 6 |
testing strategy | 6 |
distance pattern | 6 |
economic restrictions | 6 |
mai indexes | 6 |
specific diseases | 6 |
recent decades | 6 |
use patterns | 6 |
discriminant analysis | 6 |
wuhan municipal | 6 |
immigrant women | 6 |
mass testing | 6 |
based study | 6 |
uk pst | 6 |
different social | 6 |
individual level | 6 |
unemployment rate | 6 |
poverty level | 6 |
likelihood model | 6 |
expression analysis | 6 |
obtained using | 6 |
ata declaration | 6 |
stage renal | 6 |
clinical practice | 6 |
daily number | 6 |
sectional study | 6 |
rural district | 6 |
insurance coverage | 6 |
per person | 6 |
disease threats | 6 |
modified behaviors | 6 |
among host | 6 |
intensity physical | 6 |
aids outcomes | 6 |
municipal population | 6 |
use drugs | 6 |
false negative | 6 |
health action | 6 |
across human | 6 |
foster care | 6 |
pilot project | 6 |
year period | 6 |
partial differential | 6 |
survival probabilities | 6 |
hosts may | 6 |
street pump | 6 |
individual heterogeneity | 6 |
analysis shows | 6 |
parasite transmission | 6 |
population increases | 6 |
dynamics within | 6 |
sin nombre | 6 |
models based | 6 |
health measure | 6 |
benefit analysis | 6 |
population inside | 6 |
police power | 6 |
major components | 6 |
scenario analysis | 6 |
evolutionary forces | 6 |
pedigree studies | 6 |
past decade | 6 |
assess whether | 6 |
posterior probability | 6 |
emerging disease | 6 |
offspring distribution | 6 |
parasite resistance | 6 |
may vary | 6 |
treatment programs | 6 |
different parts | 6 |
within countries | 6 |
small fraction | 6 |
education level | 6 |
variable gender | 6 |
natural enemy | 6 |
bayesian analysis | 6 |
disease incidence | 6 |
transcriptome sequencing | 6 |
behavioral needs | 6 |
infected patients | 6 |
accelerated development | 6 |
see supplementary | 6 |
emerging diseases | 6 |
rna polymerase | 6 |
family physician | 5 |
random effects | 5 |
well described | 5 |
control region | 5 |
qualitative data | 5 |
also provides | 5 |
immune individuals | 5 |
genital carcinoma | 5 |
network dynamics | 5 |
significant effects | 5 |
source populations | 5 |
housed cats | 5 |
human caregivers | 5 |
paq analyses | 5 |
epidemic modeling | 5 |
house mouse | 5 |
include social | 5 |
global climate | 5 |
new opportunities | 5 |
reverse transcription | 5 |
daily confirmed | 5 |
software package | 5 |
three decades | 5 |
also influence | 5 |
major health | 5 |
functional groups | 5 |
food web | 5 |
urban regions | 5 |
age children | 5 |
care provision | 5 |
rural counterparts | 5 |
parameters using | 5 |
viral extinction | 5 |
may seem | 5 |
confidence level | 5 |
many patients | 5 |
emerging threats | 5 |
pathogen persists | 5 |
geographic distance | 5 |
serious health | 5 |
save lives | 5 |
novel pathogens | 5 |
disposable income | 5 |
slightly greater | 5 |
ncov outbreak | 5 |
cause population | 5 |
differentiation among | 5 |
term control | 5 |
highly conserved | 5 |
core law | 5 |
anthropogenic activities | 5 |
tested negative | 5 |
creative commons | 5 |
proxy variable | 5 |
antibody response | 5 |
viral hepatitis | 5 |
asymptomatic cases | 5 |
routine screening | 5 |
term business | 5 |
families originate | 5 |
traditional epidemiological | 5 |
urban agriculture | 5 |
dead individuals | 5 |
pathogenic microorganisms | 5 |
population first | 5 |
five steps | 5 |
largest number | 5 |
rate curve | 5 |
rural status | 5 |
deterministic model | 5 |
cash income | 5 |
provide adequate | 5 |
estimated using | 5 |
new paradigm | 5 |
ml min | 5 |
progress towards | 5 |
particularly relevant | 5 |
among youth | 5 |
also lead | 5 |
tertiary industrial | 5 |
wheat yellow | 5 |
waiting time | 5 |
species diversity | 5 |
mosquito control | 5 |
owner reunification | 5 |
branch lengths | 5 |
urban women | 5 |
junior high | 5 |
health characteristics | 5 |
care professionals | 5 |
adult females | 5 |
three types | 5 |
diverse population | 5 |
start date | 5 |
sample survey | 5 |
immunity will | 5 |
disaster situations | 5 |
related deaths | 5 |
future health | 5 |
animal reservoir | 5 |
genetic population | 5 |
time required | 5 |
tukey post | 5 |
higher rate | 5 |
risks associated | 5 |
industrial output | 5 |
cluster i | 5 |
will ensure | 5 |
health regulations | 5 |
epidemiological modelling | 5 |
geographical location | 5 |
many cities | 5 |
migration data | 5 |
living environment | 5 |
travel time | 5 |
rate increases | 5 |
viral epidemics | 5 |
population differentiation | 5 |
homo sapiens | 5 |
based models | 5 |
may develop | 5 |
rate variation | 5 |
following system | 5 |
will share | 5 |
care workers | 5 |
supportive care | 5 |
political will | 5 |
policy changes | 5 |
european union | 5 |
measles vaccination | 5 |
different influence | 5 |
cause acute | 5 |
agricultural production | 5 |
study shows | 5 |
pathogen genomes | 5 |
based policy | 5 |
make predictions | 5 |
may even | 5 |
increasingly important | 5 |
hiv treatment | 5 |
bayesian posterior | 5 |
effective use | 5 |
several countries | 5 |
electronic health | 5 |
specific needs | 5 |
worm disease | 5 |
different target | 5 |
driven models | 5 |
independent factors | 5 |
social context | 5 |
higher number | 5 |
many shelters | 5 |
extreme weather | 5 |
typhoid fever | 5 |
humanitarian crisis | 5 |